Dr. Google to Dr. ChatGPT: assessing the content and quality of artificial intelligence-generated medical information on appendicitis.

INTRODUCTION: Generative artificial intelligence (AI) chatbots have recently been posited as potential sources of online medical information for patients making medical decisions. Existing online patient-oriented medical information has repeatedly been shown to be of variable quality and difficult readability. Therefore, we sought to evaluate the content and quality of AI-generated medical information on acute appendicitis. METHODS: A modified DISCERN assessment tool, comprising 16 distinct criteria each scored on a 5-point Likert scale (score range 16-80), was used to assess AI-generated content. Readability was determined using the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) scores. Four popular chatbots, ChatGPT-3.5 and ChatGPT-4, Bard, and Claude-2, were prompted to generate medical information about appendicitis. Three investigators independently scored the generated texts blinded to the identity of the AI platforms. RESULTS: ChatGPT-3.5, ChatGPT-4, Bard, and Claude-2 had overall mean (SD) quality scores of 60.7 (1.2), 62.0 (1.0), 62.3 (1.2), and 51.3 (2.3), respectively, on a scale of 16-80. Inter-rater reliability was 0.81, 0.75, 0.81, and 0.72, respectively, indicating substantial agreement. Claude-2 demonstrated a significantly lower mean quality score compared to ChatGPT-4 (p = 0.001), ChatGPT-3.5 (p = 0.005), and Bard (p = 0.001). Bard was the only AI platform that listed verifiable sources, while Claude-2 provided fabricated sources. All chatbots except for Claude-2 advised readers to consult a physician if experiencing symptoms. Regarding readability, FKGL and FRE scores of ChatGPT-3.5, ChatGPT-4, Bard, and Claude-2 were 14.6 and 23.8, 11.9 and 33.9, 8.6 and 52.8, 11.0 and 36.6, respectively, indicating difficulty readability at a college reading skill level. CONCLUSION: AI-generated medical information on appendicitis scored favorably upon quality assessment, but most either fabricated sources or did not provide any altogether. Additionally, overall readability far exceeded recommended levels for the public. Generative AI platforms demonstrate measured potential for patient education and engagement about appendicitis.

Pancreatic Neuroendocrine Tumors: Signaling Pathways and Epigenetic Regulation.

Pancreatic neuroendocrine tumors (PNETs) are characterized by dysregulated signaling pathways that are crucial for tumor formation and progression. The efficacy of traditional therapies is limited, particularly in the treatment of PNETs at an advanced stage. Epigenetic alterations profoundly impact the activity of signaling pathways in cancer development, offering potential opportunities for drug development. There is currently a lack of extensive research on epigenetic regulation in PNETs. To fill this gap, we first summarize major signaling events that are involved in PNET development. Then, we discuss the epigenetic regulation of these signaling pathways in the context of both PNETs and commonly occurring-and therefore more extensively studied-malignancies. Finally, we will offer a perspective on the future research direction of the PNET epigenome and its potential applications in patient care.

The contribution of household income to rectal cancer patient characteristics, treatment, and outcomes from 2010 to 2020.

Background: There is a paucity of recent literature investigating the sole effect of income level on the treatment and survival of patients with rectal cancer. Methods: We analyzed all cases of rectal cancer in the Rectal Cancer PUF of the NCDB from 2010 to 2020. We utilized the Median Income Quartiles 2016-2020 to define our income levels. The two lower quartiles were combined to create a lower income group, with the upper two quartiles creating the higher income group. The total cohort included 201,329 patients, with 116,843 and 84,486 in the higher and lower income groups, respectively. Results: Lower income patients were more often black (17 % vs 6 %), lived farther from the nearest hospital (33.5 miles vs 25.7 miles) despite being more likely to live in urban areas (25 % vs 7 %), and had lower levels of private insurance (36 % vs 49 %). They underwent more APRs (17 % vs 14 %) and had a 13 % higher chance of undergoing an open operation (OR 1.13, CI 1.09-1.17). Higher income patients had a 12 % reduction in 90-day (OR 0.88, 95 % CI 0.82-0.96) and overall mortality (OR 0.88, 95 % CI 0.86-0.89). Conclusions: Clinicians should be aware that lower income patients are often faced with unique challenges that may impact care delivery.

An Atypical Presentation of Gonococcal Endocarditis.

A 53-year-old male presented following cardiac arrest, followed by cardiopulmonary resuscitation. He was found to have myocardial infarction, bihemispheric cerebral embolization and mitral valve endocarditis. Mitral valve replacement was performed and Neisseria gonorrhoeae was detected on PCR. This case represents a valuable addition to the limited reports on gonococcal endocarditis.

Can Artificial Intelligence Improve the Readability of Patient Education Materials on Aortic Stenosis? A Pilot Study.

INTRODUCTION: The advent of generative artificial intelligence (AI) dialogue platforms and large language models (LLMs) may help facilitate ongoing efforts to improve health literacy. Additionally, recent studies have highlighted inadequate health literacy among patients with cardiac disease. The aim of the present study was to ascertain whether two freely available generative AI dialogue platforms could rewrite online aortic stenosis (AS) patient education materials (PEMs) to meet recommended reading skill levels for the public. METHODS: Online PEMs were gathered from a professional cardiothoracic surgical society and academic institutions in the USA. PEMs were then inputted into two AI-powered LLMs, ChatGPT-3.5 and Bard, with the prompt "translate to 5th-grade reading level". Readability of PEMs before and after AI conversion was measured using the validated Flesch Reading Ease (FRE), Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook Index (SMOGI), and Gunning-Fog Index (GFI) scores. RESULTS: Overall, 21 PEMs on AS were gathered. Original readability measures indicated difficult readability at the 10th-12th grade reading level. ChatGPT-3.5 successfully improved readability across all four measures (p < 0.001) to the approximately 6th-7th grade reading level. Bard successfully improved readability across all measures (p < 0.001) except for SMOGI (p = 0.729) to the approximately 8th-9th grade level. Neither platform generated PEMs written below the recommended 6th-grade reading level. ChatGPT-3.5 demonstrated significantly more favorable post-conversion readability scores, percentage change in readability scores, and conversion time compared to Bard (all p < 0.001). CONCLUSION: AI dialogue platforms can enhance the readability of PEMs for patients with AS but may not fully meet recommended reading skill levels, highlighting potential tools to help strengthen cardiac health literacy in the future.